A model of tuberculosis clustering in low incidence countries reveals more transmission in the United Kingdom than the Netherlands between 2010 and 2015

Tuberculosis (TB) remains a public health threat in low TB incidence countries, through a combination of reactivated disease and onward transmission. Using surveillance data from the United Kingdom (UK) and the Netherlands (NL), we demonstrate a simple and predictable relationship between the probability of observing a cluster and its size (the number of cases with a single genotype). We demonstrate that the full range of observed cluster sizes can be described using a modified branching process model with the individual reproduction number following a Poisson lognormal distribution. We estimate that, on average, between 2010 and 2015, a TB case generated 0.41 (95% CrI 0.30,0.60) secondary cases in the UK, and 0.24 (0.14,0.48) secondary cases in the NL. A majority of cases did not generate any secondary cases. Recent transmission accounted for 39% (26%,60%) of UK cases and 23%(13%,37%) of NL cases. We predict that reducing UK transmission rates to those observed in the NL would result in 538(266,818) fewer cases annually in the UK. In conclusion, while TB in low incidence countries is strongly associated with reactivated infections, we demonstrate that recent transmission remains sufficient to warrant policies aimed at limiting local TB spread.

[1]  N. Nagelkerke,et al.  Analysis of tuberculosis transmission between nationalities in the Netherlands in the period 1993-1995 using DNA fingerprinting. , 1998, American journal of epidemiology.

[2]  D. van Soolingen,et al.  Molecular epidemiology of tuberculosis in the Netherlands: a nationwide study from 1993 through 1997. , 1999, The Journal of infectious diseases.

[3]  P E Fine,et al.  The long-term dynamics of tuberculosis and other diseases with long serial intervals: implications of and for changing reproduction numbers , 1998, Epidemiology and Infection.

[4]  Matt J. Keeling,et al.  Social encounter networks: collective properties and disease transmission , 2012, Journal of The Royal Society Interface.

[5]  Xavier Didelot,et al.  Bayesian Inference of Infectious Disease Transmission from Whole-Genome Sequence Data , 2014, Molecular biology and evolution.

[6]  D. van Soolingen,et al.  Progress towards tuberculosis elimination: secular trend, immigration and transmission , 2010, European Respiratory Journal.

[7]  Marcel A Behr,et al.  Proportion of tuberculosis transmission that takes place in households in a high-incidence area , 2004, The Lancet.

[8]  N. Becker,et al.  On parametric estimation for mortal branching processes , 1974 .

[9]  M Schulzer,et al.  Risk factors for clustering of tuberculosis cases: a systematic review of population-based molecular epidemiology studies. , 2008, The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease.

[10]  Colin S Gillespie,et al.  Fitting Heavy Tailed Distributions: The poweRlaw Package , 2014, 1407.3492.

[11]  D. van Soolingen,et al.  Transmission and Progression to Disease of Mycobacterium tuberculosis Phylogenetic Lineages in The Netherlands , 2015, Journal of Clinical Microbiology.

[12]  Ellen Brooks-Pollock,et al.  Epidemiologic inference from the distribution of tuberculosis cases in households in Lima, Peru. , 2011, The Journal of infectious diseases.

[13]  A. Dirksen,et al.  Risk of Mycobacterium tuberculosis Transmission in a Low-Incidence Country Due to Immigration from High-Incidence Areas , 2001, Journal of Clinical Microbiology.

[14]  Franck Jabot,et al.  EasyABC: a R package to perform ecient approximate Bayesian computation sampling schemes , 2015 .

[15]  David Welch,et al.  Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems , 2009, Journal of The Royal Society Interface.

[16]  I. Bygbjerg,et al.  Migrant tuberculosis: the extent of transmission in a low burden country , 2012, BMC Infectious Diseases.

[17]  Stefan Niemann,et al.  Whole genome sequencing of Mycobacterium tuberculosis , 2018, European Respiratory Journal.

[18]  E. Hamblion,et al.  Recent household transmission of tuberculosis in England, 2010–2012: retrospective national cohort study combining epidemiological and molecular strain typing data , 2017, BMC Medicine.

[19]  Richard G. White,et al.  An evaluation of tuberculosis contact investigations against national standards , 2017, Thorax.

[20]  Dick van Soolingen,et al.  Tuberculosis Elimination in the Netherlands , 2005, Emerging infectious diseases.

[21]  Tuberculosis outbreak investigation using phylodynamic analysis , 2018, Epidemics.

[22]  Mark E. J. Newman,et al.  Power-Law Distributions in Empirical Data , 2007, SIAM Rev..

[23]  R. Anderson,et al.  Power laws governing epidemics in isolated populations , 1996, Nature.

[24]  Hansjakob Furrer,et al.  Standard Genotyping Overestimates Transmission of Mycobacterium tuberculosis among Immigrants in a Low-Incidence Country , 2016, Journal of Clinical Microbiology.

[25]  Andrew R Francis,et al.  Interpreting genotype cluster sizes of Mycobacterium tuberculosis isolates typed with IS6110 and spoligotyping. , 2008, Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases.

[26]  Daniel J. Wilson,et al.  Whole-genome sequencing to delineate Mycobacterium tuberculosis outbreaks: a retrospective observational study , 2013, The Lancet. Infectious diseases.

[27]  L. F. White,et al.  Quantifying TB transmission: a systematic review of reproduction number and serial interval estimates for tuberculosis , 2018, Epidemiology and Infection.

[28]  P. E. Kopp,et al.  Superspreading and the effect of individual variation on disease emergence , 2005, Nature.

[29]  A. Le Menach,et al.  Recent TB transmission, clustering and predictors of large clusters in London, 2010–2012: results from first 3 years of universal MIRU-VNTR strain typing , 2016, Thorax.

[30]  C. Beck,et al.  Social network analysis and whole genome sequencing in a cohort study to investigate TB transmission in an educational setting , 2019, BMC Infectious Diseases.

[31]  J. Wallinga,et al.  A Sign of Superspreading in Tuberculosis: Highly Skewed Distribution of Genotypic Cluster Sizes , 2013, Epidemiology.

[32]  M. Borgdorff,et al.  Coverage and yield of tuberculosis contact investigations in the Netherlands. , 2011, The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease.

[33]  M. Bulmer On Fitting the Poisson Lognormal Distribution to Species-Abundance Data , 1974 .

[34]  E. Williamson,et al.  Tuberculosis in migrants moving from high-incidence to low-incidence countries: a population-based cohort study of 519 955 migrants screened before entry to England, Wales, and Northern Ireland , 2016, The Lancet.

[35]  S. Gagneux Host–pathogen coevolution in human tuberculosis , 2012, Philosophical Transactions of the Royal Society B: Biological Sciences.

[36]  M. Lalor,et al.  Understanding Tuberculosis Transmission in the United Kingdom: Findings From 6 Years of Mycobacterial Interspersed Repetitive Unit–Variable Number Tandem Repeats Strain Typing, 2010–2015 , 2018, American journal of epidemiology.

[37]  Ellen Brooks-Pollock,et al.  A dynamic model of bovine tuberculosis spread and control in Great Britain , 2014, Nature.